Systemic Inflammatory Indicators and Risk of Incident Metabolically Unhealthy Phenotype.

This retrospective cohort study was designed to evaluate the association between eight systemic inflammation indicators at baseline and the metabolically unhealthy (MU) phenotype after two years of follow-up. Methods: Participants were defined as metabolically healthy (MH) if they met 0– 2 of the criteria and metabolically unhealthy (MU) if they met ≥ 3 of the criteria. A many of 4175 subjects aged 20– 80 years with a metabolically healthy (MH) phenotype at baseline were enrolled in the study. We compared the clinical characteristics between women and men enrolled at baseline according to the metabolic phenotype at follow-up. The associations between baseline inflammation indicators and MU status at follow-up were evaluated using logistic regression analysis. Results: 922 (22.08%) developed new-onset MU symptoms during follow-up. Logistic regression analysis found that most inflammation indicators were significantly associated with MU phenotype at follow-up, aside from the LMR and SII. After adjusting for potential confounders, only the correlations between CRP level, neutrophil count, and MU phenotype reached significance. In comparison to the control group with a CRP of < 0.50 mg/L, the odds ratios (ORs) and 95% confidence intervals (CIs) were 1.61 (1.25– 2.09), 1.49 (1.15– 1.94), and 1.68 (1.30– 2.18) for individuals with CRP levels of 0.50– 0.90 mg/L, 0.91– 1.72 mg/L, and above 1.72 mg/L, respectively. In the population with a neutrophil count < 5.00 × 10⁹ cells/L, the neutrophil count correlated positively and significantly with the MU phenotype. In comparison to the control group with a neutrophil count of < 2.75 × 10⁹ cells/L, the ORs and 95% CIs were 1.65 (1.30– 2.09) in the population with neutrophil count > 4.17 × 10⁹ cells/L. Conclusion: CRP and neutrophil counts positively correlated with the risk of MU phenotype in Chinese subjects. These composite inflammatory markers (NLR, PLR, LMR, and SII) provide limited advantages for predicting MU risks compared to CRP. [ABSTRACT FROM AUTHOR]